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  1. 5861

    Node selection based on label quantity information in federated learning by Jiahua MA, Xinghua SUN, Wenchao XIA, Xijun WANG, Hongzhou TAN, Hongbo ZHU

    Published 2021-12-01
    “…Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.…”
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    Article
  2. 5862

    Electricity Demand Projection Using a Path-Coefficient Analysis and BAG-SA Approach: A Case Study of China by Qunli Wu, Chenyang Peng

    Published 2017-01-01
    “…The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. …”
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    Article
  3. 5863

    Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

    Published 2025-03-01
    “…This study employed multiple machine learning models to perform risk prediction and result exploration for first-trimester Down syndrome in East Asian populations, aiming to identify an optimal risk prediction model that will enhance future predictions of Down syndrome risk and improve the efficiency of the screening process.Patients and Methods: This study collected data from the Down syndrome screening database at Taipei Chang Gung Memorial Hospital from May 1, 2018, to February 29, 2024. …”
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    Article
  4. 5864

    Breast Tumor-Like-Masses Segmentation From Scattering Images Obtained With an Ultrahigh-Sensitivity Talbot-Lau Interferometer Using Convolutional Neural Networks by Ionut-Cristian Ciobanu, Nicoleta Safca, Elena Anghel, Dan Popescu

    Published 2025-01-01
    “…Future work will focus on optimizing CNN architecture and expanding the dataset to improve the segmentation of small tumor-like masses.…”
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    Article
  5. 5865

    Reliable Event Detection via Multiple Edge Computing on Streaming Traffic Social Data by Yipeng Ji, Jingyi Wang, Yan Niu, Hongyuan Ma

    Published 2025-01-01
    “…Then, we utilize graph neural networks to perform semi-supervised learning on HIN to obtain the optimal meta-path weights. We also develop Binary Sample Graph Convolutional Neural Network (BS-GCN) and Binary Sample Graph Attention Network (BS-GAT) to improve the reliability of graph neural network models based on the characteristics of traffic event detection and design an incremental clustering algorithm based on event similarity to implement streaming social traffic event detection. …”
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    Article
  6. 5866

    Node selection based on label quantity information in federated learning by Jiahua MA, Xinghua SUN, Wenchao XIA, Xijun WANG, Hongzhou TAN, Hongbo ZHU

    Published 2021-12-01
    “…Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.…”
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    Article
  7. 5867

    “Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

    Published 2025-01-01
    “…The correction has the most significant impact in northwestern Zhejiang, while its effects are less pronounced in the northeastern coastal areas. (2) Both overall correction and regional correction improve forecast accuracy across various precipitation thresholds. …”
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    Article
  8. 5868

    Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

    Published 2024-12-01
    “…However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. …”
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    Article
  9. 5869

    Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

    Published 2023-12-01
    “…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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    Article
  10. 5870

    Discussing the Construction of a Budget Management System Combining Multimedia Technology and Financial Risk Management by Xiaoyi Jiang

    Published 2022-01-01
    “…In the traditional support vector machine, when the test sample is located at the boundary point of the hyperplane, the judgment may be wrong. In the aspect of SVM model improvement, according to the discrimination method of SVM, the weighted K-nearest neighbor algorithm is introduced to redistinguish the qualified test samples in the feature space. …”
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    Article
  11. 5871

    Manufacturing engineering production line scheduling management technology integrating availability constraints and heuristic rules by Gu Yun

    Published 2025-06-01
    “…The above results indicate that the proposed model and hybrid algorithm have good performance and effectiveness, which can help improve the quality of engineering production line scheduling management.…”
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    Article
  12. 5872

    Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

    Published 2025-04-01
    “…This study introduces innovative ensemble learning models that integrate the randomizable filter classifier (RFC), regression by discretization (RBD), and attribute-selected classifier (ASC) with the random forest (RF) algorithm, resulting in hybrid models (RFC-RF, RBD-RF, and ASC-RF). …”
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    Article
  13. 5873

    An Effective ABC-SVM Approach for Surface Roughness Prediction in Manufacturing Processes by Juan Lu, Xiaoping Liao, Steven Li, Haibin Ouyang, Kai Chen, Bing Huang

    Published 2019-01-01
    “…To improve the prediction accuracy and reduce parameter adjustment time of SVM model, artificial bee colony algorithm (ABC) is employed to optimize internal parameters of SVM model. …”
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    Article
  14. 5874

    Power Allocation for 5G Mobile Multiuser Cooperative Networks by Fagen Yin, Wencai Du

    Published 2021-01-01
    “…To solve the optimization problem, we propose an intelligent power allocation optimization algorithm based on grey wolf optimization (GWO). …”
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    Article
  15. 5875

    Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

    Published 2021-01-01
    “…Finally, optimization results of a real-world logistics network from Chongqing confirm the applicability of the mathematical model and the designed solution algorithm. …”
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    Article
  16. 5876

    A New Method for Solving Supervised Data Classification Problems by Parvaneh Shabanzadeh, Rubiyah Yusof

    Published 2014-01-01
    “…To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. …”
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    Article
  17. 5877

    A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

    Published 2021-07-01
    “…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
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    Article
  18. 5878

    High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

    Published 2025-02-01
    “…The Back Propagation Nondominated Sorting Genetic Algorithm-II (BP-NGA) model consistently yielded positive results for most WQI. (2) Water quality in Dianchi varied significantly by region and season. (3) It was recommended to build wetlands and ecological parks on the southwest side of Dianchi and improve sewage interception pipelines on the northeast side to lessen the risk of eutrophication by reducing the inflow of nitrogen and phosphorus.…”
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  19. 5879

    An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language by Hasan et al.

    Published 2019-06-01
    “…This method demonstrated improved accuracy of data collected, reduced data processing time and arranged data to the willing model.…”
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    Article
  20. 5880

    Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

    Published 2025-06-01
    “…Faster RCNN and Yolov8 were used to compare the performance of object detection, and the loss function and accuracy curve before and after model improvement were compared. The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
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    Article